The present invention relates to the area of electronic information systems. In particular, the present invention relates to a method and system for the delivery of financial information using resampled statistical methods over an information network.
Investors and financial analysts rely upon electronic information systems for the delivery of accurate financial and investment data and analysis in order to devise meaningful investment strategies. The growth of the Internet and World Wide Web (xe2x80x9cWWWxe2x80x9d) highlights the potential for global distribution of xe2x80x9creal timexe2x80x9d or xe2x80x9cnear real timexe2x80x9d financial information and analysis. For example, a number of WWW sites provide financial information to clients such as investors and financial analysts.
However, conventional financial information sites do not provide meaningful analysis tools to accurately analyze, forecast and predict the behavior of financial markets. Conventional technology for delivery of financial information over information networks such as the Internet typically allows users to track returns for various investments and perform rudimentary statistical analysis (e.g., computation of the mean and standard deviation) for these investments. However, these rudimentary statistical functions are not useful to investors in forecasting the behavior of financial markets because they rely upon assumptions that the underlying probability distribution function (xe2x80x9cPDFxe2x80x9d) for the financial data follows a normal or Gaussian distribution, which is generally false.
The true distribution of returns for any financial market (and thus of a trading strategy) is unknown. It is therefore incorrect to rely upon a statistical model based on assumptions of normality (e.g., standard deviation). Typically, the PDF for financial market data is heavy tailed (i.e., the histograms of financial market data typically involve many outliers containing important information). Thus, statistical measures such as the standard deviation provide no meaningful insight into the distribution of financial data.
Providing reasonable methods for the analysis of financial market data is essential for investors. Reasonable statistical analysis of financial data should at a minimum provide an accurate assessment of potential financial risk and reward. However, conventional methods, which rely upon assumptions of a Gaussian distribution, are dangerous to investors because these analyses understate the true risk and overstate potential rewards for an investment or trading strategy. Thus, this information is not generally useful and if relied upon promotes imprudent investment decisions. In general, the heavy tailed nature of financial data presents significant challenges in providing meaningful statistical analysis.
The present invention provides a method and system for the statistical analysis, display and dissemination of financial data over an information network such as the Internet and WWW. The present invention utilizes resampled statistical methods for the analysis of financial data. Resampled statistical analysis provides a meaningful and reasonable statistical description of financial information, which typically escapes modeling using parametric methods (i.e., assumptions of a Gaussian distribution).
The present invention includes a financial information network node that is coupled to an information network such as the Internet. The financial information network node includes a front end subsystem, a resampled statistical analysis engine (xe2x80x9cRSAExe2x80x9d) and a graphics rendering engine (xe2x80x9cGRExe2x80x9d). The front end subsystem provides a graphical user interface (xe2x80x9cGUIxe2x80x9d) that allows clients also coupled to the information network to submit requests for resampled statistical analysis of various financial investments and receive graphical display of the results. The RSAE performs resampled statistical analysis of financial data in response to user queries and incorporates routines to preserve temporal correlation in financial data, which necessarily provides more accurate analysis. In addition, the RSAE provides for user control of a number of parameters to simulate various financial environmental conditions. For example, according to one embodiment, the RSAE allows a user to simulate either bull or bear market conditions by setting a bias parameter that controls a degree of randomness in the resampling process. The GRE generates a graphical display of statistical distributions generated by the RSAE.
According to one embodiment, the present invention employs a parallel processing architecture to speed generation of the resampled statistics. The parallel architecture is afforded by the nature of the resampling algorithm itself, which permits the financial data to be vectorized. This parallel processing architecture provides at least two significant advantages. First, the architecture permits the delivery and processing of financial data in compressed time frames, which facilitates xe2x80x9creal timexe2x80x9d or xe2x80x9cnear real timexe2x80x9d statistical analysis. In addition, the parallel computation scheme provides the ability to perform statistical analysis on a large number of financial entities (e.g., a mutual fund or hedge fund) through a weighting process.
According to one embodiment of the present invention for implementation on the Internet, a financial information site is coupled to the Internet via a front end subsystem including a WWW server. The financial information site includes a front end subsystem, a RSAE and a GRE. In addition, the financial information site maintains a database of financial data for any number of financial entities such as companies, mutual funds etc. The financial information site also maintains a database of clients that have registered with the financial information site and desire to obtain statistical analysis of financial data.
In order to perform a resampled statistical analysis, a query is received from a client via the front end subsystem. A client may specify a number of parameters including an investment or investments (e.g., a portfolio) to be analyzed, a financial function, a sample size, a period, a type of plot and a bias parameter, which controls the randomness of the resampling process. Based upon the parameters specified by the client, the RSAE performs a resampled statistical analysis of relevant financial data. The GRE then produces a distribution plot based upon the output generated by the RSAE, which is presented to the client via the front end subsystem.
According to one embodiment of the present invention, the RSAE performs at least three types of financial functions on financial data. A gross rate of return function provides analysis of the gross rate of returns for an investment over a specified time period. A maximum drawdown function provides analysis of a maximum drawdown for an investment over a specified period. A monitor function provides analysis of a number of xe2x80x9cupxe2x80x9d and xe2x80x9cdownxe2x80x9d days for a particular investment over a period of time.
The financial information site also provides functionality for storing a set of client specified alert rules that are used to automatically monitor the behavior of investments based upon a resampled statistical analysis process and notify clients of the financial information site when the behavior of a particular investment violates a specified rule.